title: The relationship between the visual evoked potential and the gamma band investigated by blind and semi-blind methods.
abstract: Gamma Band Activity (GBA) is increasingly studied for its relation with attention, change detection, maintenance of working memory and the processing of sensory stimuli. Activity around the gamma range has also been linked with early visual processing, although the relationship between this activity and the low frequency visual evoked potential (VEP) remains unclear. This study examined the ability of blind and semi-blind source separation techniques to extract sources specifically related to the VEP and GBA in order to shed light on the relationship between them. Blind (Independent Component Analysis-ICA) and semi-Blind (Functional Source Separation-FSS) methods were applied to dense array EEG data recorded during checkerboard stimulation. FSS was performed with both temporal and spectral constraints to identify specifically the generators of the main peak of the VEP (P100) and of the GBA. Source localisation and time-frequency analyses were then used to investigate the properties and co-dependencies between VEP/P100 and GBA. Analysis of the VEP extracted using the different methods demonstrated very similar morphology and localisation of the generators. Single trial time frequency analysis showed higher GBA when a larger amplitude VEP/P100 occurred. Further examination indicated that the evoked (phase-locked) component of the GBA was more related to the P100, whilst the induced component correlated with the VEP as a whole. The results suggest that the VEP and GBA may be generated by the same neuronal populations, and implicate this relationship as a potential mediator of the correlation between the VEP and the Blood Oxygenation Level Dependent (BOLD) effect measured with fMRI.
authors.affiliation: Institute of Neuroscience, Newcastle University, Medical School, Framlington Place, Newcastle upon Tyne, UK. camillo.porcaro@newcastle.ac.uk
authors.forename: Camillo
authors.initials: C
authors.lastname: Porcaro
authors.forename: Dirk
authors.initials: D
authors.lastname: Ostwald
authors.forename: Avgis
authors.initials: A
authors.lastname: Hadjipapas
authors.forename: Gareth R
authors.initials: GR
authors.lastname: Barnes
authors.forename: Andrew P
authors.initials: AP
authors.lastname: Bagshaw
mesh_terms: D000328:Adult; D000465:Algorithms; D000513:Alpha Rhythm / Q000502:physiology; D001611:Beta Rhythm / Q000502:physiology; D001921:Brain / Q000502:physiology; D001931:Brain Mapping; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D004566:Electrodes; D004569:Electroencephalography / Q000379:methods* / Q000706:statistics & numerical data*; D005074:Evoked Potentials, Visual / Q000502:physiology*; D005260:Female; D006801:Humans; D008297:Male; D025341:Principal Component Analysis; D015203:Reproducibility of Results